Post navigation

Untangling cancer’s genetic trajectory

Untangling cancer’s genetic trajectory

The new study in Nature tracks the evolution of a breast cancer, a diagnosis that becomes more common with age.

Genetically, cancer is a mess. Tumor cells don’t do the work of a healthy cell, but they are awfully good at making sloppy copies of themselves. Removed from the normal restraints and error-checking that keep healthy cells honest, cancer cells can change over time as they evolve to fight the immune system and cancer drugs.

Until now, getting a picture of these genetic changes has been an insurmountable task. Just “reading” the normal DNA in one person cost billions and took about a decade. But now, techniques for hyperspeed DNA sequencing are starting to produce libraries of genetic data, raising the hope of unraveling the varying genetics of cancer.

Nature is now reporting the most thorough study of evolution in a single patient’s breast cancer. “This week, for the first time, we have looked in detail at the evolution of a cancer genome over time,” says Samuel Aparicio, a professor at the BC [British Columbia] Cancer Research Center and the paper’s senior author. The study compared the cancer’s genes before and after it had spread, nine years later.

One disease, or many?

The ability to look in detail at cancer genes raises the prospect of eventually understanding the cause of the many diseases we call cancer. Cancer is a curious beast, and its genetics can get more bizarre with time. In the Aparicio study, the tumor cells nine years after diagnosis showed 32 significant mutations, only five of which were common in the original tumor.

Understanding the genetics of cancer could help in prevention and in treatment.

Understanding these early and late mutations could shed light on the origin and spread of cancer.

High-speed sequencing could eventually help doctors select treatments based on the genetics of the cells in the tumor, and Aparicio says his team has already begun tracking patient’s genes. “We will be able to build up our idea of what mutations might be conferring resistance or sensitivity to drugs. Eventually, we can ask, ‘did this or that genome respond better to this drug?’”

Making treatment decisions could be complicated, however, as even the original tumor showed genetic weirdness that is not found in healthy tissue. This genetic diversity is important, Aparicio says. “When one considers developing a therapeutic strategy, we tend to regard the cancer genome as a single entity. Cancer biologists have known this for decades, but we just have not had the means to see it.”

Moral of the story: Weapons against a “single” cancer are actually confronting multiple foes, which have — or may evolve — multiple genetic tricks for evading cancer-killing medicines and the immune system.

Sequencing DNA relies upon matching pairs of components that have specific preferences for partners. If you know the sequence on one strand, you can predict the sequence of the other.

Consequential sequencing system

Scientists have wanted to understand the changing genetics of cancer for decades, but this study was only possible due to phenomenal advances in sequencing speed that are meanwhile causing the cost to drop, some say, faster than the price of computers.

Ultra-speed “synthesis DNA sequencing” relies on DNA’s ladder-shaped, double-stranded structure. The molecule is built of pairs of components called “bases” that are picky about partners: The base nicknamed “A” will only link to “T”. Likewise, “G” is specific to “C.”

Any time you see a C, you know it’s got to be linked to a G. So knowing the sequence on one strand tells you the sequence on its complementary strand.

Technicians start synthesis sequencing by splitting the DNA ladder lengthwise and anchoring millions of short strands to a sample plate. The sequencing machine then introduces new bases and watches as they complete the anchored strands. Because each base will only link to its complementary pair member, the process of attachment shows the structure of the DNA fragments that were originally attached to the plate.

Synthesis sequencing is just catching on, and the current study looked at one tumor, from one patient. To understand which mutations are most dangerous, “one really has to … look at multiple cancers,” Aparicio says.

However, one mutation that already seems portentous is HAUS3, which causes defects in proteins that organize the chromosomes as they undergo the delicate process of uncoiling, duplicating, and recoiling during cell division, Aparicio says. “We know from other studies that if we deplete those proteins, cell division becomes error-prone, which leads to instability in the genome, so conceivably mutations in those genes might have been involved in the early stages of cancer.”

The secondary cancer, called a metastasis, is more likely to cause death than the primary tumor.

A first look

As an early look into the tangled genomics of cancer, the study is a good first step, says Michael Gould, an oncologist at the University of Wisconsin-Madison School of Medicine and Public Health. “In this data from one patient, the original tumor had a lot fewer meaningful mutations than previous reports on breast cancer cell lines. If this holds up for other solid tumors, and I believe it will, there will not be a huge catalog of mutations in any individual [primary] tumor, and that’s good.”

However, Gould adds that compared to a previous study of the blood cancer leukemia, the British Columbia study also found more genetic change over time. “In leukemia, the primary and metastatic tumors had the same spectrum of mutations, and people concluded there was not necessarily genetic evolution going on, that maybe when the cancer first comes up, you either have a metastatic mutation or you don’t. In this [breast cancer] study, and maybe it’s generalizable to other solid tumors, there is some evolution going on between the primary and metastatic tumor.”

As Aparicio says, the treatment goal of this type of genomic analysis is already beginning, as researchers try to correlate different genetics with treatment outcomes. But learning about gene damage in the primary tumor may also identify the original cause of the cancer. Whether that cause resides in the environment or the patient, such insights should become the basis for better cancer prevention.